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Data Literacy in Practice

You're reading from Data Literacy in Practice A complete guide to data literacy and making smarter decisions with data through intelligent actions

Product type Paperback

Published in Nov 2022

Publisher Packt

ISBN-13 9781803246758

Length 396 pages

Edition 1st Edition

Concepts

Data Analysis

Authors (2):

Kevin Hanegan

Angelika Klidas

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1: Understanding the Data Literacy Concepts

2. Chapter 1: The Beginning – The Flow of Data FREE CHAPTER

3. Chapter 2: Unfolding Your Data Journey

4. Chapter 3: Understanding the Four-Pillar Model

5. Chapter 4: Implementing Organizational Data Literacy

6. Chapter 5: Managing Your Data Environment

7. Part 2: Understanding How to Measure the Why, What, and How

8. Chapter 6: Aligning with Organizational Goals

9. Chapter 7: Designing Dashboards and Reports

10. Chapter 8: Questioning the Data

11. Chapter 9: Handling Data Responsibly

12. Part 3: Understanding the Change and How to Assess Activities

13. Chapter 10: Turning Insights into Decisions

14. Chapter 11: Defining a Data Literacy Competency Framework

15. Chapter 12: Assessing Your Data Literacy Maturity

16. Chapter 13: Managing Data and Analytics Projects

17. Chapter 14: Appendix A – Templates

18. Chapter 15: Appendix B – References

19. Index

Why subscribe?

20. Other Books You May Enjoy

Mitigating typical data and analytics project risks

What are the common risk factors that we have to manage in our data and analytics projects? When it comes to data and analytics projects, we have some typical risks to take care of. We can divide them into four categories:

Project risks
Technical risks
Culture risks
Content risks

Managing the risks of projects is important. It’s not only difficult to discuss, collect, and describe the project risks—you’ll also have to think about how to avoid them and address countermeasures. We mention high potential risks in our plans (project plan and business case), but we will have a risk register for all risks. We do this with the following method: what is the chance that this risk will occur and what is the impact of that risk when it occurs? From a project management point of view, managing risks is complex and can be challenging.

Project risks

Project risks are common risks that can occur...

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Authors (2)

Angelika Klidas

Angelika Klidas

Angelika is a highly skilled denizen of the Data world. As operations manager for several organizations, strategic advisor and Data Literacy evangelist, she is able to analyze BI & Analytics environments expertly, map the ambitions of organizations and deliver cutting-edge advice to help organizations mature their data use. Inspiring organizations and people to grow in Business Intelligence & Analytics maturity is her passion. In addition to teaching at the University of Applied Sciences in Amsterdam, where she spreads her knowledge and passion to her Data & Analytics students

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Kevin Hanegan

Kevin Hanegan

Kevin has helped individuals and organizations maximize the value they receive from their data for over 20 years. He is a is a frequent speaker and thought leader on topics including data literacy, data-informed decision making, decision intelligence, and essential skills for today's workforce. He is currently the Chief Learning Officer at Qlik, a data and analytics company, as well as the chair of the advisory board for The Data Literacy Project. Kevin is also an accomplished author of multiple books, including Turning Data into Wisdom, which helps individuals learn strategies to make data-informed decisions. He applies his passion both in the corporate setting and also in academia where he is an adjust professor at Boise State University.

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